HBS Digital Initiative builds community and expertise around digital transformation and tech at Harvard Business School and beyond. We manage this forum to gather and share perspectives from the HBS student community.

Activity Feed

Thanks for writing about this topic. In order for UNICEF to do no harm while partnering with external organizations, they will need to set clear guidelines on the nature of these partnerships. These partnerships should center on providing UNICEF with inputs they would not otherwise have — Facebook’s anonymized Zika data is a great example. What UNICEF does with these inputs should solely be in UNICEF’s control. This is where UNICEF can set rigid boundaries such as not experimenting with at-risk constituents.

On another note, I am a bit weary of providing a repository of data to the public. If this data can be anonymized like Facebook’s Zika scenario, then UNICEF can effectively balance both open innovation and privacy. What is complicated is everyone has their own tolerance of privacy, so UNICEF may experience backlash from some constituents.

Thank you for writing about this. As an uncle with a 6-year old niece, I have experienced the toy purchasing decision multiple times every year. When I examine my own purchasing behavior, I see that I have been influenced by what my niece thinks is the “hottest”, most popular toys / brands out there, e.g. Hatchimals, Frozen, etc. I’ve realized that children are very impressionable by what’s popular in the media they consume and at school. The reservation I have with open innovation in toys is that it seems more geared towards the adult enthusiast who can appreciate newer more innovative toy ideas. I am curious what the market share % breakdown is in toys purchased for kids vs adult enthusiast. If there is a large enough market potential for adult enthusiasts, then I think open innovation can help LEGO grow.

Interesting topic! I do not think the slow growth of the chocolate industry can be fully reversed through 3-D chocolate customization. Instead, I believe this trend speaks to an increasingly health-conscious society. It’s interesting to see Hershey’s expand into meat bars “as more consumers pore over food labels to find healthier, protein-packed snacks” (https://qz.com/665148/as-americans-eat-less-chocolate-hersheys-begins-pushing-meat-bars/). 3-D chocolate printing is a nice-to-have niche product offering for Hershey’s, but they should not invest too much in a declining chocolate category.

Thank you for writing about this. The biggest stat that jumped out in this piece is that Adidas is able to manufacture only 1M via 3-D printing out of 360M pairs sold, even with its new and faster printing process. Until 3-D printing can scale up to match traditional manufacturing output, I see this as a niche product offering for customers that want a high level of customization.

Nike is also entering this 3-D printing space (https://www.engadget.com/2018/04/17/nike-flyprint/). Their product, the FlyPrint, is only produced in a limited run for now. If Adidas can ramp up 3-D printing faster, can they surpass Nike in innovation?

I believe there is a lot of potential in personalized nutrition with FitBit and other biometric tracking devices. The co-founder of a 3-D food printer has said “You [could] connect your Fitbit to your food printer and it can print a breakfast bar, for example, that’s appropriate for you on that given day,” (https://www.businessinsider.com/3d-printed-food-foodini-2016-4). The devices already exist (FitBit, 3-D food printers); what still needs to be refined to make this a reality is the recommendation engine that links biometrics to nutrition, and the communication ability between these two different devices.

Thanks for writing about this. If / when other teams start partnering with IBM Watson, I believe the aspects mentioned of “scouting reports, medical histories and personality evaluations derived from interviews and social media for cultural fit” will become the primary differentiators in teams’ judgments of certain players; machine learning is taking out the human judgment for the quantitative measures of a player’s performance.

The use of machine learning in coaching is fascinating. Could there be one day no coaches, and only an algorithm that recommends precise lineups and plays? I don’t think this will manifest – there is still a human element of a leader in sports that is valuable in motivating a team.